Machine Learning Engineer

Founded in 2016, VoxelCloud, Inc.is a Los Angeles-based worldwide leader in AI analysis ofmedical images. Backed bySequoia and Tencent. We help healthcare providers make better/earlier diagnoses and related clinical decisions, improving outcomes for all.http://www.voxelcloud.ai Job Description The R&D team (located in Los Angeles, CA) is involved with research and development ofinnovative solutions to medical imaging applications, including disease detection/quantification in medical scans, disease risk stratification, image synthesis, text report mining, and more!

We are currently hiring both full-time and interns to join our R&D team. Responsibilities: Developdeep learning models for prototyping and production purposes according to product feature request Design, implement and testmodel experiments using major deep learning frameworks Document experiments findings and results withsupporting summary statisticsfor peer discussion and review (Confluence) Provide insights to data collection and annotation and collaborate with the data team for in-house data management and labelling Write production and deployment code (dockerization), iterate deployedmodels for optimal performance and inference speed Conduct methodology research in deep learning to drive scalable, real-time implementation Qualifications Basic Qualifications MS degree in computer science, engineering, or mathematics 2-3years of relevant experience in building deep learning solutions for computer vision problems Proficient with at least one major deep learning framework, preferablyTensorFlow/Pytorch Proficient in Python Good CS fundamentals in data structures and algorithm Detail-oriented, well organized and self-motivated with a continuous drive to learn, explore and be challenged Work well in teams and communicateideas clearly Preferred Qualifications PhD degree in computer science, engineering, or mathematics 3-5years of relevant experience in building deep learning solutions for computer vision problems Hands-on experience with state-of-the-art object detection (e.g., RetinaNet, Mask RCNN, CenterNet), semantic segmentation (e.g., U-Net, deeplab), and image classification models (e.g., ResNet, DenseNet). Track record of publications in CV and medical image analysis is a plus Hands-on experience with model optimization (e.g., network quantization and mixed-precision training) is a plus Prior experience with medial images is a plus Additional Information Transparent, collaborative work environment; Competitive compensation Excellent Medical, Dental, and Vision coverage 401k, paid Vacation and Holiday All your information will be kept confidential according to EEO guidelines. #J-18808-Ljbffr